Tablet computers are often called upon to emulate classical pen-and-paper input. However, most touch devices today lack palm rejection features—most notably the highly popular Apple iPad tablets. Failure to reject palms effectively in a pen or touch input system results in ergonomic issues, accidental activation and unwanted inputs, precluding fluid and efficient use of these input systems. This issue is well known in the prior art.
Presently, the most reliable way to disambiguate stylus input from human input is to use special hardware. For example, ultrasonic transducers can be placed at the periphery of a screen to sense ultrasonic pulses emitted by an active pen. It is also possible to use an infrared emitting pen and two or more cameras to triangulate the planar position on a screen. Yet another method uses a passive capacitive tip, which simulates a finger touch. The pen itself is powered and pressure sensitive, sending data to the device over Bluetooth. With timing information, it is possible to associate touch events with pen down events.
Another approach known in the prior art, uses resonance inductive coupling, which uses a special pen and sensor board that operates behind the conventional capacitive touchscreen. This technology is used in devices such as the Microsoft Surface and Samsung Galaxy Note. Similarly, another method uses a grid of Hall Effect sensors behind the touchscreen to sense the magnetic tip of a special pen. Also known is the use of a grid of infrared proximity sensors and computer vision to separate palm and finger inputs. Finally, advanced capacitive touchscreens can differentiate passive styli by looking at contact size and capacitive properties.
Even with special hardware for stylus support, simply distinguishing pen from finger is insufficient if the finger can still be used for input. In this case, unwanted palm touches may still be interpreted as finger touches in the absence of the pen. Thus, software is still needed to reliably distinguish pens and fingers from palms, which the above solutions do not address.
Although special styli tend to offer excellent precision, a significant downside is the need for a special purpose accessory, which is often platform-specific. Further, additional internal hardware is often required to support these pens, adding to the build cost, size and power draw of mobile devices. Thus, a software-only solution, which can be easily deployed and updated, is attractive. Further, software solutions offer the ability to disambiguate between finger and palm input. However, without an innate way to disambiguate touch events, software solutions must rely on clever processing or interaction techniques.
For optical multi-touch devices, one approach is to identify palm regions visible from the camera image. On mobile devices with capacitive screens, the task is more challenging, since applications generally do not have access to a hand image, or even the capacitive response of the touch screen. Instead, applications must rely on information about touch position, orientation (if available), and size. There are dozens of applications in the iOS and Android app stores that claim to have palm rejection features. Unfortunately, none of them adequately address the problem of palm rejection.
One method known in the art is to specify a special ‘palm rejection region’ where all touches are ignored, though this is unwieldy. Unfortunately, palm touches outside the input region can still provide accidental input (e.g. accidental button presses). One known method makes use of a more sophisticated geometric model to specify the rejection region, providing a five-parameter scalable circle and pivoting rectangle, which captures the area covered by the palm better than a rectangular region.
A second approach uses spatiotemporal features—looking at the evolution of touch properties and movement over a short time window. We hypothesize that applications that first draw, then remove strokes, must wait some period of time before detecting accidental touches. Prior art applications require the user to specify information regarding their handedness orientation and to use the tablet in a fixed orientation. Additionally, one prior art application requires users to specify one of three handwriting poses they use.